Object Recognition

Object recognition is a computer vision technique for detecting + classifying objects in images or videos. Since this is a combined task of object detection plus image classification, the state-of-the-art tables are recorded for each component task here and here.

( Image credit: Tensorflow Object Detection API )

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 1931–1940 of 2042 papers

Title	Date	Tasks	Status	Hype
Performance Evaluation of Raster Based Shape Vectors in Object Recognition	Mar 28, 2014	ObjectObject Recognition	—Unverified	0
Scene Labeling with Contextual Hierarchical Models	Feb 4, 2014	Edge DetectionImage Segmentation	—Unverified	0
A Unifying Framework in Vector-valued Reproducing Kernel Hilbert Spaces for Manifold Regularization and Co-Regularized Multi-view Learning	Jan 31, 2014	MULTI-VIEW LEARNINGObject Recognition	—Unverified	0
Learning Human Pose Estimation Features with Convolutional Networks	Dec 27, 2013	Object RecognitionPose Estimation	CodeCode Available	0
OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks	Dec 21, 2013	General ClassificationImage Classification	CodeCode Available	1
Unsupervised Feature Learning by Deep Sparse Coding	Dec 20, 2013	Object Recognition	—Unverified	0
Using Web Co-occurrence Statistics for Improving Image Categorization	Dec 19, 2013	Common Sense ReasoningImage Categorization	—Unverified	0
Some Improvements on Deep Convolutional Neural Network Based Image Classification	Dec 19, 2013	ClassificationGeneral Classification	CodeCode Available	2
Unsupervised feature learning by augmenting single images	Dec 18, 2013	Data AugmentationObject Recognition	—Unverified	0
Scalable Object Detection using Deep Neural Networks	Dec 8, 2013	Objectobject-detection	CodeCode Available	0

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All datasets shape bias CIFAR10-DVS N-Caltech 101 ObjectNet (All classes)ObjectNet (ImageNet classes)ObjectNet (ImageNet classes, trained on ImageNet)DVS128 Gesture MECCANO N-CARS

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	Imagen	shape bias	98.7	—	Unverified
2	Stable Diffusion	shape bias	92.7	—	Unverified
3	Parti	shape bias	91.7	—	Unverified
4	ViT-22B-384	shape bias	86.4	—	Unverified
5	ViT-22B-560	shape bias	83.8	—	Unverified
6	CLIP (ViT-B)	shape bias	79.9	—	Unverified
7	ViT-22B-224	shape bias	78	—	Unverified
8	ResNet-50 (L2 eps 5.0 adv trained)	shape bias	69.5	—	Unverified
9	ResNet-50 (with strong augmentations)	shape bias	62.2	—	Unverified
10	SWSL (ResNeXt-101)	shape bias	49.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Spike-VGG11	Accuracy (% )	85.55	—	Unverified
2	SSNN	Accuracy (% )	78.57	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Spike-VGG11	Accuracy (% )	85.62	—	Unverified
2	SSNN	Accuracy (% )	79.25	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ObjectNet-Baseline	Top 5 Accuracy	18.75	—	Unverified
2	yun	Top 5 Accuracy	14.75	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ObjectNet-Baseline	Top 5 Accuracy	52.24	—	Unverified
2	DY	Top 5 Accuracy	0.08	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ObjectNet-Baseline	Top 5 Accuracy	52.24	—	Unverified
2	AJ2021	Top 5 Accuracy	27.68	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SSNN	Accuracy (% )	94.91	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Faster-RCNN	mAP	30.39	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Spike-VGG11	Accuracy (% )	96	—	Unverified